Learn Object Detection Tracking and Counting with DL, ML

Name: Learn Object Detection Tracking and Counting with DL, ML
Rating: 3.4 (47 reviews)

Object Detection, Tracking & Counting with OpenCV, Tensorflow, dlib, Machine Learning , Deep Learning

Last updated 2/2021

English

What you'll learn

9 sections • 19 lectures • 2h 10m total length

Object Detection Tracking Counting Part-0113:40
Here we are using the dlib you can follow the following steps to install dlib

For Mac
$ ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
$ brew update
$ echo -e "\n# Homebrew" >> ~/.bash_profile
$ echo "export PATH=/usr/local/bin:$PATH" >> ~/.bash_profile
$ source ~/.bash_profile
$ brew install python python3
$ pip install numpy
$ pip install dlib
Object Counting Part-02 - Person Detection Tracking and Counting - IN OUT16:50
You will learn to write code for Person counting moving inside or outside from a specific position.
You need to install dlib extra and simply can install by $ pip install dlib command to run this code.

Introduction of Object Detection, Counting & Tracking
Installation of all prerequisites to write the code for object detection, counting & tracking on Mac Machine
Workflow and System Architecture
Write and Run the Code for
- Write and Run the code for object detection, tracking and counting with dlib
- Write and Run the code for object detection using deep learning with OpenCV
- Write and Run the Code for Cumulative Counting of Objects in Video
- Write and Run the Code for Real-Time Counting of Objects
- Write and Run Code for Object Tracking
- Detect the targeted or all objects
- Count the targeted or all objects
- Predict the colour of targeted or all objects
- Predict the speed of targeted or all objects
- Export results in csv file